Methods capable of determining marking stripes demarcating road lanes are commonly used in systems for aiding vehicle guidance. Such methods, as described, for example, in "Parallel and Local Feature Extraction: A Real-Time Approach to Road Boundary Detection," A. Broggi--IEEE Transactions On Image Processing, Vol. 4, No. 2, February 1995, pp. 217-223, typically comprise a phase of low-level filtering which extracts the relevant characteristics from the road image, followed by a phase of high-level analysis which determines a representation of the marking stripes. Rather simple processing techniques, which exhibit a low computational cost, capable of identifying the discontinuities present in the road image are generally used in the low-level filtering phase. For example, the image is subjected to a mathematical convolution operation with a suitable mask (or kernel) matrix, and the result is compared with a specified threshold value. The mask always exhibits very small dimensions, as in the case of the Prewitt operator, consisting of a matrix of three rows and three columns of ternary elements (-1, 0, +1). Such techniques, however, also pick out the outlines associated with various objects present in the image, for example, other vehicles, road signs, shadows, and the like (noise). They therefore require the use of complex high-level analyses for eliminating noise, with heavy demands for computational power.
Other techniques, such as the use of geometrical models described in "A Morphological Model-Driven Approach to Real-Time Road Boundary Detection for Vision-Based Automotive Systems," A. Broggi, S. Berte--Proc. Second IEEE Workshop on Applications of Computer Vision, pp. 73-90, Dec. 5-7, 1994--IEEE Computer Society, transform the image on the basis of a predefined model so as then to determine the representation of the marking stripes of the road lanes. Such transformations have, however, to be applied over extensive portions of the image and require the use of rather complex basic operations. They therefore need large processing resources and cannot be carried out efficiently by means of standard digital systems.
What is needed is a method for identifying marking stripes demarcating road lanes which obviates the aforesaid drawbacks.